THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR
The adoption of Artificial Intelligence (AI) in the financial sector is fundamentally transforming credit risk assessment and reshaping business models. This paper explores the impact of AI-driven technologies on credit evaluation, highlighting the shift from traditional, human-based credit scor...
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| Format: | Article |
| Language: | English |
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Academica Brâncuşi
2024-12-01
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| Series: | Analele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie |
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| Online Access: | https://www.utgjiu.ro/revista/ec/pdf/2024-06/23_Ciumara.pdf |
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| author | CIUMARA TUDOR |
| author_facet | CIUMARA TUDOR |
| author_sort | CIUMARA TUDOR |
| collection | DOAJ |
| description | The adoption of Artificial Intelligence (AI) in the financial sector is fundamentally transforming credit risk
assessment and reshaping business models. This paper explores the impact of AI-driven technologies on credit
evaluation, highlighting the shift from traditional, human-based credit scoring systems to machine learning algorithms
capable of analyzing vast amounts of structured and unstructured data. By incorporating non-traditional data sources,
AI offers a more inclusive and accurate assessment of borrower risk, potentially expanding access to credit for
underbanked populations. Furthermore, AI's ability to detect fraud and automate decision-making processes leads to
increased operational efficiency for financial institutions. However, the implementation of AI also introduces ethical
challenges, including concerns about algorithmic transparency and bias. The paper addresses these issues, proposing
that a balance between technological innovation and regulatory oversight is crucial for fostering responsible AI use in
lending. Moreover, AI is transforming business models in the financial sector by enabling personalized product
offerings and streamlining operational costs, positioning financial institutions to compete more effectively in a rapidly
evolving marketplace. This study concludes by discussing future trends, such as the integration of AI with blockchain
technologies and the increasing collaboration between traditional banks and fintech firms. These developments are
expected to further drive innovation and redefine the landscape of credit risk management. |
| format | Article |
| id | doaj-art-85b4a6ab74164e0798c255e302953eb9 |
| institution | Kabale University |
| issn | 1844-7007 2344-3685 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Academica Brâncuşi |
| record_format | Article |
| series | Analele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie |
| spelling | doaj-art-85b4a6ab74164e0798c255e302953eb92025-01-01T11:34:05ZengAcademica BrâncuşiAnalele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie1844-70072344-36852024-12-0116199203THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR CIUMARA TUDOR 0PHD, “VICTOR SLĂVESCU” CENTER FOR FINANACIAL AND MONETARY RESEARCH The adoption of Artificial Intelligence (AI) in the financial sector is fundamentally transforming credit risk assessment and reshaping business models. This paper explores the impact of AI-driven technologies on credit evaluation, highlighting the shift from traditional, human-based credit scoring systems to machine learning algorithms capable of analyzing vast amounts of structured and unstructured data. By incorporating non-traditional data sources, AI offers a more inclusive and accurate assessment of borrower risk, potentially expanding access to credit for underbanked populations. Furthermore, AI's ability to detect fraud and automate decision-making processes leads to increased operational efficiency for financial institutions. However, the implementation of AI also introduces ethical challenges, including concerns about algorithmic transparency and bias. The paper addresses these issues, proposing that a balance between technological innovation and regulatory oversight is crucial for fostering responsible AI use in lending. Moreover, AI is transforming business models in the financial sector by enabling personalized product offerings and streamlining operational costs, positioning financial institutions to compete more effectively in a rapidly evolving marketplace. This study concludes by discussing future trends, such as the integration of AI with blockchain technologies and the increasing collaboration between traditional banks and fintech firms. These developments are expected to further drive innovation and redefine the landscape of credit risk management.https://www.utgjiu.ro/revista/ec/pdf/2024-06/23_Ciumara.pdfartificial intelligencecredit risk assessmentfinancial sectorbusiness model transformation |
| spellingShingle | CIUMARA TUDOR THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR Analele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie artificial intelligence credit risk assessment financial sector business model transformation |
| title | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR |
| title_full | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR |
| title_fullStr | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR |
| title_full_unstemmed | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR |
| title_short | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR |
| title_sort | impact of artificial intelligence on credit risk assessment and business model transformation in the financial sector |
| topic | artificial intelligence credit risk assessment financial sector business model transformation |
| url | https://www.utgjiu.ro/revista/ec/pdf/2024-06/23_Ciumara.pdf |
| work_keys_str_mv | AT ciumaratudor theimpactofartificialintelligenceoncreditriskassessmentandbusinessmodeltransformationinthefinancialsector AT ciumaratudor impactofartificialintelligenceoncreditriskassessmentandbusinessmodeltransformationinthefinancialsector |